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Perennial energy crops for semiarid lands in the Mediterranean: Elytrigia elongata, a C3 grass with summer dormancy to produce electricity in constraint
environments
Emiliano Maletta*1, Carlos Martin-Sastre
2, Pilar Ciria
1, Aranzazu del Val
1, Annabel Salvado4,
Laura Rovira4, Rebeca Díez3, Joan Serra4, Yolanda González-Arechavala2 and Juan Carrasco
1
1 CEDER-CIEMAT. Energy Department. Biomass Unit. Autovía de Navarra A-15, salida 56. 42290 Lubia
(Soria). Phone: +34 975281013 2 Institute for Research in Technology (IIT) - ICAI School of Engineering - Comillas Pontifical University - E-
28015, Madrid (SPAIN) 3 ITACyL. Biofuels and Bioproducts Resarch Centre, Pol. Agroindustrial Par.2-6 (24358), Leon, Spain. Phone/fax:
+34-987374554 4 IRTA, Mas Badia (17134) Girona, Spain. Phone: +34- 972780275, Fax: +34-972780517
* Corresponding author: [email protected]
The aim of this report is to demonstrate and evaluate the potential of tall wheatgrass (Elytrigia elongata) to avoid
GHG emissions and obtain lower economic costs in marginal areas of Spain. Our research built scenarios based on
experimental plots (2 and 3 years growth) in 3 locations of Spain with completely different climate conditions
(provinces of Girona, Soria and Palencia). In our experiences, we achieved an adequate establishment and biomass
production, and assumed a rank of biomass yields until the end of the life cycle that is usually accepted to be about
15 years in many other studies in United States, Argentina and Eastern Europe where tall wheatgrass is extensively
cultivated in marginal areas for sheep livestock production. Using our experimental plots and statistical information
for economic inputs costs, we built 5 different scenarios per region considering a large range of biomass yields of tall
wheatgrass. The analysis included a comparison with annual grasses economic costs calculated for a wide range of
biomass yields of a previous study. We estimated GHG emissions savings for tall wheatgrasses and used our previous
study (which had GHG emissions savings as well). Savings were calculated replacing natural gas electricity with
electricity from biomass combustion in real power plants in Spain. In a wide range of yields, the results suggest that
marginal areas might present a better performance with tall wheatgrass compared to annual winter grasses (cereals
whole plant cuttings), thus producing biomass yields with higher GHG savings and lower economic costs at the farm
level.
1 INTRODUCTION
In Spain, a country with more than 4M ha with potential
for energy crops as a consequence of liberalization and
Common Agricultural Policy reforms [1], the
development of energy crops to produce biomass for
heating or electric applications represents a major
challenge. The extensive semiarid rainfed areas of the
Mediterranean require species that tolerate severe
frequent droughts during late spring and summer and
produce sufficiently high yields to obtain biomass with
low costs and high environmental benefits in relation
with the used inputs and fossil energy.
Economic constraints affecting renewable energies
are usually cited as important barriers when developing
new activities in rural areas. Moreover, biomass
production marginal costs in Spain are still a major
constraint limiting the expansion of new facilities at the
time that recent measures have cut subsidies and financial
aid for private companies [2].
During the last decade, in Spain some new power
energy plants started to produce electricity from solid
agricultural residues [3]. Biomass bales from herbaceous
crops are currently used for co-firing to produce
electricity in power energy plants. The first raw materials
considered were agricultural residues (mostly cereal straw
in square bales with less than 11% humidity) and biomass
from energy crops were then also included. Winter
annual crops like triticale (triticosecale sp.), oats (Avena
sativa), peas (Pisum sativum) and rye (Secale cereale)
but also warm annual grasses like fodder maize (Zea
maize) and fibre sorghum (sorghum bicolor), are now
typical solid biofuels involved in private contracts
between farmers and energy companies. These contracts
often establish biomass prices as high as 85€/odt for
square bales from these annual crops [4]. Therefore many
stakeholders are developing a strong interest in new
perennial energy crops that could produce lower biomass
costs in both irrigated and rain fed areas. Biomass yields
per hectare are closely linked to biomass costs since
many areas have low yields as most Mediterranean
extensive rain fed areas have low competitive lands
(unfertile soils, scares rains in spring and summer, etc.).
This consideration would be fundamental in order to
allow the economic feasibility of biomass power energy
plants in Spain.
Despite of economic considerations, energy crops
producing liquid or solid biofuels require to produce
environmental benefits regarding global warming
potentials (GWP) and greenhouse gases emissions (GHG)
among many other impact categories often studied in Life
cycle assessments (LCA) of energy crops and bioenergy
chains [5, 6]. Several studies have encouraged the
research and development of perennial species as energy
crops for marginal areas in order to produce biomass
yields with high energy balances and low environmental
impact regarding water, nitrogen use, erosion,
biodiversity and GHG emissions [7, 8].
In 2009, the Renewable Energy Directive (RED)
established increasingly restrictive minimum GHG
emissions savings for biofuels replacing fossil reference
fuels for transport. This minimums savings are 35%
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(from 2009) and will become in 50% in 2017 and 60%
from 1stJanurary of 2018 [9]. Since then, several studies
have provided evidences that marginal areas might
produce also marginal biomass yields or have logistics
implications producing low or none environmental
benefits from feedstock, residues and energy crops [5, 8,
10]. The RED also established a methodological
approach for LCA for biofuels, nevertheless solid
biomass standards and a sustainability criteria for them
have not been addressed sufficiently at the time that many
debates, recommendations on methods and discussions
on land use changes effects on GHG calculations are
currently taking place [11]. Recent significant
advancements have added new principles such as those
from the Roundtable on Sustainable Biofuels (RSB) for
certification schemes. The RSB included a new
certification scheme for most biomass and biofuel
feedstock and established a calculation method for GHG
emissions from agriculture considering CO2, NOx, N2O,
nitrates and Ammonia derived from fertilizers
production, application and dynamics in the soil [12].
In Spain electricity from lignocellulosic energy crops
may replace electricity from natural gas, the cleanest
substituted fossil source as suggested by RSB and RED.
In Spain only few publications on LCA have addressed
lignocellulosic energy crops [13, 14] and there is a lack
of information on C3 or C4 perennial grasses scenarios
producing energy. In a previous study [13], we analysed
GHG emissions from triticale, oats and rye cultivated in
continental rain fed areas in Spain in a wide range of
biomass yields from different species and varieties. Our
results suggested that cereal bales (grain+straw) have to
outreach a yield of about 8 odt/ha in order to accomplish
similar sustainability criteria established for liquid
biofuels in the RED (from 2018, 60% of GHG savings
compared to the fossil substituted reference). Therefore,
those results suggested to condition sustainability of
biomass in most agricultural arable lands in Spain that
have semiarid climate conditions and produce an average
national grain yield of 1,8 t/ha; whole plant biomass
yields of 4 odt/ha considering local harvest indexes
reported from experimental networks [15].
Additionally, many reports strongly suggest that
Common Agricultural Reforms (CAP) for 2014 health
check, should encourage perennial grasses and renewable
energy alternatives at the time cereals and dairy milk
quota would have shorten subsidies for farmers [16].
Spain as one of the member countries with more
abandoned and low competitive cereal lands of Europe
might require new alternative crops to be cultivated under
rain fed conditions and produce biomass. There is a
current need for additional plots and LCA with perennial
species suited for marginal lands or in those areas where
traditional agriculture and livestock production have low
and very low competitiveness [17].
Among several alternative crops, many perennial
grasses have been studied as energy crops and may
produce high environmental benefits and low biomass
costs at the farm level that are relevant for their
consideration on bioenergy chains [4, 5, 6, 7].
Nevertheless, early autumn and spring rains in the
Mediterranean regions are very scarce and in most
regions they limit the adequate establishment and annual
productivity of best suited energy crops like Panicum
virgatum, Arundo donax or Miscanthus giganteum. As
many other C4 grasses (four carbon photosynthetic
metabolism pathway, usually known as “warm grasses”)
these crops have yields reported to be higher than 20
odt/ha per year during their lifetime [4, ]. Nevertheless
most of them require irrigation for rhizome propagation
or event direct sowings in most agricultural lands at least
during the establishment (spring) when drought events
are very frequent in Spain limiting their viability to the
irrigation arable surface. Additionally, even when they
produce much more biomass yields, in some cases have a
higher establishment cost reported to be as high as
2000€/ha in Miscanthus [19, 20].
Perennial C3 grasses (three-carbon photosynthetic
metabolism pathway) also called “cool grasses” can be
established without irrigation during autumn or early
spring and may produce forage in successive years with
harvests during late summer when less precipitation
occur in the Mediterranean. Forage traditional crops like
reed canary grass (Phalaris sp), tall fescue (Festuca
arundinacea) or perennial ryegrass (Lolium perenne)
have been extensively used in Europe for livestock
production and also as new energy crops [21].
Nevertheless, in Mediterranean and semiarid areas most
species produce too low yields or do not re-grow after the
extreme summer drought events. Other best suited C3
energy grass is giant reed (Arundo donax) with very high
yields but require rhizomes or shoots for propagation and
even irrigation or some rains during establishment [20].
Then most of these grasses are best suited for sub-humid
areas in northern regions of Spain, not allowing most rain
fed low competitive cereal regions to produce biomass
from perennial species.
Elytrigia elongata (Host) which common name is
“Tall wheatgrass”, is also known as Thinopyrum
ponticum (Podp), Agropyron elongatum (Host); Elymus
elongatus (Host) var.ponticum. It is a summer dormant
cool season perennial grass native from Eurasia and has
been cultivated in constraints environments all over the
world [22]. Among many other similar wheatgrasses such
as Elymus lancelolatus, Pascopyron smithii, Agropyron
cristatum, A. intermedium and A. sibericum, tall
wheatgrass is probably the latest-maturing wheatgrass
adapted to the temperate areas of North America and
Europe and probably the most productive of all [22]. The
species is adapted to range sites receiving at least 300mm
of annual precipitation and is particularly noted for its
capacity to produce forage and persist in areas that are
too alkaline or saline for other productive crops [22, 23].
Thus, it is a good source of pasture and hay during the
late summer, when forage often is in short supply. It also
has been used successfully as a silage crop. Tall
wheatgrass has large seed that is easy to harvest and
plant. It has good seedling vigour, and established plants
have an exceptionally deep root system, which
contributes to its resistance to drought [23]. Its
palatability for livestock is low at the same time that it
could have acceptable characteristics to use for
combustion in industrial boilers to produce electricity
power. Some recent European studies have analysed Tall
wheatgrass and encourage its consideration for semiarid
areas as a novel energy crop [24].
The aim of this report, is to use current experimental
plots in three regions of Spain established two (2010) and
three years (2009) ago for building scenarios considering
their expected lifetime. We compared tall wheatgrass and
previously reported annual grasses performance on GHG
emissions savings when producing electricity in existing
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Spanish power energy plants and their economic costs at
the farm level in a wide assumed range of yields in the
three study regions.
2 MATERIALS AND METHODS
2.1 Location, climate and soil of the experimental plots
used for scenarios building
Two groups of parcels were established with tall
wheatgrass in the provinces of Girona (located in the
region of Catalonia), and Soria and Palencia (in the
region of Castilla y Leon). All plots were cultivated
under rain fed conditions in 2009 and 2010 (Figure 1).
Figure 1: Plots with Tall Wheatgrass (Elytrigia
elongata) in the three study regions in Spain
The experimental plots took place in very different
soils (Table 1). The plots in Soria were on a loam sandy
texture soil (sand 75-85%, lime less than 10% and clay
less than 15%) with organic matter about 0.6% and pH of
6.8. This soil is light, with good drainage. The deeper
texture is sandy or sandy loam. The soil in the plots of
Palencia was the richest in P with moderately high
organic matter (1.37) and the highest pH (8.5). The plots
in the province of Girona have highest organic matter
contents (1.65%).
Table I: Soil characteristics in 0-30 cm layer of the three
sites used for scenario building in this study
pH N (%)P
(mg/kg)
K
(mg/kg)
Organic
Matter (%)Texture
Girona 8,2 0,11 28 192 1,65 loam
Palencia 8,5 0,09 50,4 0,22 1,37 Franc
Soria 6,8 0,03 6,6 61,2 0,6 sandy
Regarding climate conditions, the region of Soria is
characterized by fairly hot summers, with temperatures
sometimes reaching 30 ºC, and cold winters, with
temperatures falling below 0 ºC and frequent frosts; in
2010 the first autumn frost occurred on September 27th (–
0.4 ºC), whereas the last spring frost in 2011 took place
on March 22nd (–0.4 ºC).
The province of Girona is characterized by a Coastal
Mediterranean climate. These characteristics give to this
location more moderate temperatures with no prolonged
periods of extremely high or low temperatures. The
average annual temperature is between 15-16° C, the
minimum annual average is 7°C and the
highest is 23ºC. Extreme temperatures rarely are below
0ºC or exceed 40°C. There are generally soft winters and
hot-drought summers, which generates a lot of
accumulation of water vapor in the atmosphere which
produce “cold drop” in autumn (weather phenomenon
associated with the Mediterranean area characterized by
heavy rains, hail and electrical storms). The average
rainfall values are between 600-750mm. May occur
torrential rains in spring, but especially in autumn. This
location has less dry months than other locations of these
climate characteristics. The province of Palencia, is
characterized by a Continental Mediterranean climate.
Rainfalls range between 350 and 600 mm, the maximum
is in spring and autumn (minimum in winter and
summer). The monthly mean temperature is between 7ºC
and 19 °C with cold winters (between 5 and -10 ° C), and
dry and hot summers (between 20 and 27 ° C average
temperature). Figure 2 shows Ombrothermic diagram –
average temperature (ºC) against precipitation (mm)-
from September 2010 to August 2011.
Soria
0
10
20
30
40
50
60
70
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Months
Tem
pera
ture
(ºC
)
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Average Temperature (ºC) Precipitation (mm)
Girona
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Months
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ture
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Pre
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mm
)
Palencia
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Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Months
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ture
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)
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Pre
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(m
m)
Soria
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Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Months
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Average Temperature (ºC) Precipitation (mm)
Girona
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Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Months
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ture
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Palencia
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Pre
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itati
on
(m
m)
Figure 2: Ombrothermic diagram for the period
September 2010-August 2011 in all three sites
2.2 Experimental plots used for scenario building
The experimental parcels were established in autumn
2009 and 2010, and in both cases they had no harvests
during the establishment year.
Table II: Experimental plots from different trials (established in 2009 and 2010) in the three study regions
Palencia Soria
Girona
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Regions
Management and inputs 2009 2010 2009 2010 2009 2010
Experimental plot Strips Strips small plots Strips small plots small plots
Plot size (total in m2) 5000 4500 225 135 90 90
Tillage operations
Base (NPK in kg/ha)
1st year
Succesive years 0 250
Sowing rate 40 20 30 20 20
Sowing date Nov.2009 Nov.2010 Oct.2009 Oct.2010 Oct.2009 Oct.2010
pre-emergence none Glifosate none
post-emergence none 2-4D 2-4D and MCPA
Weed control mowings 2010 2010 2009 and 2010 2010 and 2011
Cut numbers 1 1 1 1 2 (june - Oct) 1
Biomass yield range (odt/ha) 2.5 - 6 4 - 10 5 - 12 5 - 12 12 - 39 10 - 40
300
GironaPalenciaSoria
350 500 none
Chisel, harrowing, rotary tiller
Herbicides
Top fertilizers NAC27% (kg/ha)
nonenonenone
250
Note: Yields from 2012 were estimated before harvest (June 2012). Maximum and minimum values correspond to the
extreme values of replicates in the first and second year, and in the third year in the case of trials established in 2009
Both trials (2009 and 2010) followed similar
management techniques. Operations for tillage soil
preparation were similar to those usually implemented
with cereals and annual grasses in Spain, including two
passes of chisel, one with harrow disks, rotary tiller and
ring roller. Then, a base fertilization was usually utilized
before sowing in autumn except in Girona were soils are
richer enough and typical management considers weed
competition as favoured when nitrogen fertilizers are
applied during crop establishment (table II). Sowing rates
were adjusted in relation to the germination rates and
seed viability from previous tests (data not shown).
Herbicides and weed control operations (mowing) during
establishment were followed when needed.
Figure 3: Trials plots in Soria (2009) with tall
wheatgrass during bailing in the second year
Sampling methods were used to evaluate the
production in each replicate when trials were cultivated
as small plots (Girona and Palencia). Biomass yields
including harvest losses evaluation were registered in the
grass strips of Soria by mowing and baling operations
(Figure 2). Biomass yields reported considered the
variation among trials and repetitions or replicates as well
as an estimation of the expected biomass yield to be
achieved in summer 2012. Biomass yields assumed for
the third years were based on observations and height in
June 2012.
2.3. Scenarios definition
Management, machinery operations and raw materials
Scenarios definition followed several assumptions for
the total expected lifetime of tall wheatgrass. There are
very few studies with evaluations of tall wheatgrass in a
long period of time especially without grazing
management (only grass cuttings). Many evaluations on
tall wheatgrass were intended for forage production under
extreme alkaline soil conditions that are very different
from the areas under study (mostly arable lands with low
cereal yields). Based on specific studies in other
countries, lifetime of tall wheatgrass in this assessment
was assumed to be 15 years [24]. Following this report
and our experimental plots, we assumed no harvest in the
first year, as well as a maximum yield after the third year
to be maintained for 7 years and a progressive decrease
starting after the crops has 10 years old.
Before establishment, machinery labour included
tillage operations and base broadcasting fertilizations
with NPK fertilizer in Palencia (500kg/ha). Considering
our plots in Soria, Palencia and Girona, once tall
wheatgrass was established we assumed mowing
operations during next spring in order to avoid weed
competition which is also a recommended management to
avoid excessive evapotranspiration during summer in the
first year [22]. Thus, by letting the biomass on the ground
in the first year no baling was considered.
Machinery equipment and tractors weights and
lifetime as well as diesel consumptions were taken from
the Spanish Ministry of Agriculture [25]. This
information was taken into account for the LCA and
economic costs analysis considering the number of times
of all operations during the assumed lifetime.
Fertilization during spring was also different among
the defined scenarios. Based on our experience in Soria,
no top fertilization in spring was done in the
establishment year. Fertilization with Calcium Ammonia
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Nitrate (CAN) 27% doses were assumed to be 300, 250
and 150 kg/ha for Palencia, Girona and Soria based on
the soil characteristics and yield expectancy considering
climate conditions. Additionally, a nutrient restitution to
the soil with NPK was assumed to be 50kg/ha in Palencia
and Girona, and 80kg/ha in Soria 6 times in the 15 years
lifetime of tall wheatgrass.
Other inputs like herbicides where assumed based on
the plots of the three study regions as well. Thus, the
scenario considers a pre-emergence glyphosate (1 l/ha) in
Palencia, and broadleaf herbicides 2-4D and dicamba (1
l/ha) in Soria and Palencia during the first year. A final
herbicide spreading (two passes) was also assumed for
the end of the lifetime to allow a new crop establishment
(glyphosate, 1 l/ha).
Table III: Machinery equipment and number of
operations involved in the lifetime (15years) of tall
wheatgrass Weight Lifetime Palencia Girona Soria
Machinery operations for lifetime (kg) (h)
Chisel ploughing (50cm) 750 1200 1
Harrowing by disks 1800 1200 2 2
Ring roller 1500 400 1
Chisel ploughing (25cm) 750 1200 1
Rotary tiller 1400 1200 2 2
Base fertilizer application (establishment) 700 400 1 0 0
Restitution NPK fertilizer (spreader) 700 400 6 6 6
Sowing 810 750 1 1 1
Herbicides spreader (pre-emergence) 600 500 1 0 0
Top fertilizer application (spring) 700 400 15 15 14
Herbicides spreader (post-emergence) 600 500 1 1 1
Mowing 2400 667 15 16 15
Baling (250kg bales) 9000 2308 14 14 14
Bales loading 2500 1333 14 14 14
Last herbicide (End-life application) 600 500 2 2 2
Tractor 1 (120HP) 4320 12000
Tractor 2 (150HP) 5400 10000
(times)
Yields
In order to build scenarios assuming normal large-sized
plots with tall wheatgrass in the study regions, we used
the information from our management techniques and
results in small and medium sized (strips) plots. Based on
similar practices and yields in other reports from
Argentina [26], United States [27] and Hungary [24] we
defined five yield scenarios for each region: very low,
low, middle, high and very high (Table IV). These
different yields assumed no substantial changes in
fertilization or cultivation techniques. Therefore we
assumed that variation in yields is mostly caused by soil
and climate variability among years and specific site
(parcels) of each region. Yields defined in scenarios for
large plots considered the typical differences that small
plots have because of border effects (usually large plots
present 25-50% lower yields compared to small plots
depending on boarders and plot shape).
Table IV: Yield scenarios for the three study regions
Regions Very low Low Middle High Very High
Palencia (odt/ha) 4,1 5,8 7,0 8,2 10,2
Girona (odt/ha) 6,2 8,1 9,5 10,9 12,8
Soria (odt/ha) 2,4 3,9 5,0 6,1 7,0
Yield scenarios (mean value for lifetime)
The three agronomic management patterns (one per
region) and five yield levels of our three regions reported
then a total of 15 scenarios for which economic and LCA
was carried out. The five yield levels reflect variations
assumed to be linked with soil and climate variations
(climatic year and site dependent).
2.4 Life Cycle Assessment methodologies
Life Cycle Assessment (LCA) is the environmental
tool we selected to determine the energetic and
environmental performance of Tall wheatgrass to produce
lignocellulosic biomass for electricity generation.
LCA is a systematic set of procedures for compiling
and examining the inputs and outputs of materials and
energy and the associated environmental impacts directly
attributable to the functioning of a product or service
system throughout its life cycle [28]. This environmental
assessment tool is regulated by ISO 14040 [28] and ISO
14044 [29] standards, and according to this, LCAs
should follow four steps: (1) goal and definition, (2)
inventory analysis, (3) impact assessment and (4)
interpretation.
Simapro 7.2 [30,31] software tool and Ecoinvent 2.2
[32,33] European database have been selected for the
LCAs.
Also a rough nitrogen balance was made considering
nitrogen supply by fertilizers and measuring the amount
of nitrogen contended in the crops as the nitrogen
extracted.
2.4.1 Goal and Scope definition
The aim of this study is to evaluate the energy
balance and environmental impacts of the 15 scenarios
defined in the above sections for growing tall wheatgrass
as energy crop in Spain for electricity generation and
compare them with electricity generation from natural
gas, as a reference for generation from non-renewable
fossil sources.
2.4.2. Functional unit
The functional unit chosen is 1 TJ of electrical energy
generated from biomass for the studied system and from
natural gas for the reference system. This amount of
electrical energy is a round number corresponding to 12
hours of functioning of the 25Mw power plant selected
for this study (see 2.4.5).
The electricity production per hectare of tall
wheatgrass trials is the product of the crop yield (see
Table IV) at 12 % humidity by the net calorific value at
12 % humidity [27] and by the efficiency of the biomass
conversion process into electricity (29.5 % for this case
study).
2.4.3 Systems description
The bioenergy systems analyzed includes three
subsystems: agricultural biomass production, electricity
generation and the transport of products and raw
materials.
Agricultural system
The agricultural system could be described by the
crop schemes followed, the machinery used and the
inputs consumed.
Biomass power plant system
All the data considered to model the biomass power
plant system are real data from a 25 MW biomass plant
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located in northern Spain. This plant consumes biomass
at an average humidity of 12% and produces electricity
with a conversion efficiency of 29.5%. The plant
consumes natural gas for maintenance operations and
pre-heating and produces ashes and slag from biomass as
residues. The average consumption of natural gas and the
productions of ashes and slag per kilogram of burned
biomass are shown in Table V.
Table V: Biomass power plant consumptions and
residues produced Consumed or produced
substances Amount
Natural gas consumption
(MJ Kg-1 Wet Biomass Burned)
0.0342
Slag production
(g Kg-1 Wet Biomass Burned) 82.47
Ashes production
(g Kg-1 Wet Biomass Burned)
8.25
The emissions of the plant into the air are submitted
regularly to the local government. The emissions
accounted are only those which affect the global warming
potential (GWP). In the power plant studied these
emissions come from gas natural combustion (see Table
VI). Carbon dioxide emitted from biomass combustion
was not considered because it was previously fixed from
the air by the crop.
Table VI: Biomass power plant aerial emissions Substance Origin Amount
(g Kg-1 Wet Biomass
Burned)
Fossil carbon
dioxide Natural gas 1.94
Table VII: Transport system summary Material From To Distance Vehicle
Seed Field Processing
center 30 km
Lorry
20-28t
Processing
center
Regional
storehouse 100 km
Lorry
20-28t
Regional
storehouse
Demonstratio
n parcel 10 km
Lorry
16-32t
Fertilizers
and
herbicides
Manufacturer Regional
storehouse 600 km Train
100 km Lorry
>16t
Regional
storehouse
Demonstratio
n parcel 10 km
Lorry
16-32t
Biomass Demonstratio
n parcel Biomass plant 60 km
Lorry
16-32t
Ash and
slag Biomass plant Disposal 37 km
Lorry
16-32t
Transport system
The transport system is summarized in Table VII.
This table shows all modes of transport used and the
distances between origin and destination points for every
transport in the LCAs carried out.
The transportation means and distances for the
transport of agricultural inputs until the regional
storehouse are taken from the Ecoinvent database [34].
The distance from the regional store house to plots was
10 km approximately. The transport of workers to the
parcel has not been considered because of the highly
variability of transport distances depending on cases.
Biomass, ash and slag means of transport and distances
were provided by company in charge of the biomass
power plant.
Natural gas system
The natural gas system includes the gas field
operations for extraction, the losses, the emissions and
the purification of the main exporter counties of natural
gas to Spain (Algeria 73 % and Norway 27 %). Also
includes the long distance and local transport of gas to
the power plant in Spain, considering the energy
consumption, loses and emissions for distribution.
Finally the substances needed and the average efficiency
of Spanish natural gas power plants to produce electricity
are taken into account [35].
2.4.4 Life cycle inventory analysis
The inventories used to consider natural gas
consumption [35] of the biomass power plant, transports
[36] of agricultural inputs, and biomass and power plant
residues are taken from Ecoinvent.
The methods used for the inventory analysis of the
agricultural system mainly follow that proposed on Life
cycle inventories of agricultural production systems [34].
To consider N2O emissions we follow the formula
proposed by de RSB GHG Calculation Methodology v
2.0 [12]. This formula is basically based on the formula
proposed in the Ecoinvent Agricultural Report [34], that
considers the new IPCC guidelines [37]. Also we
consider the nitrate emissions affecting to Global
Warning Potential as the RSB purposes [12], making and
estimation of them by means of nitrogen balance, the soil
and crop characteristics and the rainfall of the zone.
Fertilizers productions
The fertilizer inventories consider the different steps
of the production processes, such as the use of raw
materials and semi-finished products, the energy used in
the process, the transport of raw materials and
intermediate products, and the relevant emissions [34].
The production of calcium ammonium nitrate starts
with the production of the ammonium nitrate by the
neutralization of ammonia with nitric acid. The final
product is then obtained by adding dolomite or limestone
to the solution before drying and granulation [38].
No inventories are given in Ecoivent for multinutrient
fertilizers due to the amount different possible ways to
mix nitrogen, phosphorous and potassium compounds to
produce NPK fertilizers [38]. The modeling of NPK
fertilizer inventories has been approximated by
combining inventories of single fertilizers according to
multinutrient fertilizer specific contents of N, P2O5 and
K2O, as well as the form of the nitrogen provided
(ammonium, nitrate or urea) [38].
Herbicides production
The data related to emissions, energy and substance
consumption in the production of the herbicides sprayed
is taken from Ecoinvent [39]. The quantities of active
matters considered are taken from the formulations of the
commercial fertilizers used.
Seed production
Tall wheatgrass seeds can be produced in Spain under
similar conditions compared to the operations of fertilizer
and management practices used for forage cultivation.
Page 7
Tall wheatgrass seeds are frequently produced under
irrigation in high quality soils under contract with real
farmers, thus their normal operations and yield
production were assumed to be similar to that of the local
common management practices considered in this study.
Then, a grain production yield of 0.8 odt ha-1 was
considered as suggested by other studies [25,26,27].
The energy consumption for cleaning, drying, seed
dressing, and bag filling of the Tall wheatgrass seed in
the processing plant has been estimated in 32.8 kWh t-
1[40].
Diesel consumption and combustion emissions of
agricultural machinery
The diesel consumption of agricultural machinery
was obtained from the Spanish Ministry of Agriculture
[25]. The inventories for the extraction, transport of
petrol, the transformation into diesel and its distribution
are taken from Ecoinvent [41]. The exhaust emissions of
diesel in agricultural machinery engines are also
considered [41].
Agricultural machinery manufacture
The inventories for agricultural machinery
manufacture are specific to the different types of
machinery (tractors, harvesters, tillage implements or
general implements).
The amount of machinery (AM) needed for a specific
process was calculated multiplying the weight (W) of the
machinery by the operation time (OT) and dividing the
result by the lifetime of the machinery (LT) [34]:
AM (kg FU-1) = W (kg) OT (h FU-1) LT-1(h);
Where FU (See 2.4.2) is the functional unit of the
LCA. The life time was obtained from the Spanish
Ministery of Agriculture (see Table III) [25].
Nitrous oxide emissions
The calculation of the N2O emissions [12] is based
on the formula in Nemecek et Kägi [34] and adopts the
new IPCC guidelines [37]:
N2O=
44/28∙(EF1∙(Ntot+Ncr)+EF4∙14/17∙NH3+EF5∙14/62∙NO3-)
With:
N2O = emissions of N2O [kg N2O ha-1]
EF1 = 0.01 (IPCC proposed factor [37])
Ntot = total nitrogen input [kg N ha-1]
Ncr = nitrogen contained in the crop residues [kg N ha-1]
EF4 = 0.01 (IPCC proposed factor [37])
NH3 = losses of nitrogen in the form of ammonia [kg
NH3 ha-1]. Calculated as proposed in the RSB [12] and
Nemecek et Kägi [34] methodologies.
14/17= conversion of kg NH3 in kg NH3-N
EF5 = 0.0075 (IPCC proposed factor [37])
NO3- = losses of nitrogen in the form of nitrate [kg NO3
ha-1]. They were estimated through the RSB formula [12]
which considers nitrogen supply, the nitrogen uptake, the
soil and crop characteristics and the local rainfall.
14/62= conversion of kg NO3- in kg NO3-N.
Land use changes
Direct land used change does not take place because
the parcel selected was previously a winter cereal crop
land. Indirect land use change is a complex process that
is not fully understood by the scientific community and
so is not included in this study [43].
2.4.5 Life cycle impact assessment
Life Cycle Impact Assessment (LCIA) is the phase in
an LCA where the inputs and outputs of elementary flows
that have been collected and reported in the inventory are
translated into impact indicator results [44].
LCIA is composed of mandatory and optional steps.
Mandatory steps of classification and characterization
have been carried out and optional steps normalization
and weighting have been avoided in order to make results
more comparable and to avoid introducing value choices.
In the classification steps elementary flows shall be
assigned to those one or more impact categories to which
they contribute. In the characterization steps each
quantitative characterization factor shall be assigned to
all elementary flows of the inventory for the categories
that have been included in the classification [44].
Environmental impact assessment method
We have selected the software tool Simapro 7.2 [45]
and the impact assessment method of the IPCC 2007 [46]
to assess the 100 years’ period horizon Global Warming
Potential (GWP).
Energy assessment method
In order to assess the energy consumed to generate
electricity from tall wheatgrass biomass and from natural
gas, we have selected the software tool Simapro 7.2 [45]
and the Cumulative Energy Requirement Analysis
(CERA) [48]. This method aims to investigate the energy
use throughout the life cycle of a good or service. The
primary fossil energy (FOSE) has been obtained using
this method.
2.5. Comparison between tall wheatgrass and winter
cereals from previous studies
A previous study data and results from two
experimental plots with triticale (Triticosecale sp.), oats
(Avena sativa), lopsided oats (Avena strigosa L.) and rye
(Secale cereale) was utilized in order to make
comparisons with tall wheatgrass scenarios performance.
The 15 scenarios of tall wheatgrass were based in a
similar range of biomass yields compared to the cited
research in which GHG emissions savings when
substituting natural gas electricity by combusting biomass
in a 25MW boiler. The mentioned study considered two
sites with experimental plots located in two Spanish
provinces in Castilla y León (Soria and León). The power
energy plant and transport systems cited in tables V and
VI, were the same for both studies [13].
2.6 Economic costs at the farm level
In order to calculate costs for biomass production at
the farm level, the 15 scenarios defined for tall
wheatgrass in above sections were analysed together with
the winter cereal trials analysed in previous studies [13].
Winter cereals costs included two regions as defined in
our previous study (Soria and León) which were assumed
to explore enough yield and be management
representative for typical cereal areas in central Spain.
Rental land costs in Soria were assumed to be 90€/ha per
year when cropping Tall wheatgrass. Winter cereals
rental land costs were assumed to be an average value for
Page 8
the region of Castilla y León (119€/ha.year). Both tall
wheatgrass and winter cereals used economic data from
MARM (2012)[25] and local information for fertilizer,
herbicides and tall wheatgrass seeds prices.
2.7. Nitrogen balances
A rough nitrogen balance was made. This estimation
considers nitrogen supplied in base and top fertilizations
as the entrance of the system and total nitrogen content of
rye aerial biomass trials as exit of the system. The total
amount of nitrogen extracted and exported by the crop
harvest is calculated by multiplying the yield of each
scenario (see Table IV) by its respective biomass
nitrogen content [27]. As roots remain into the soil we
assumed that all nitrogen from roots return to the soil.
Therefore we did not take into account any proportion of
root nitrogen content as extracted nitrogen.
3 RESULTS AND DISCUSSION
3.1 Economic assessment
Costs at the farm level resulted to be much higher for
biomass production from winter cereals compared to Tall
wheatgrass (Figure 4).
0
20
40
60
80
100
120
140
160
180
200
220
240
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Me
an
bio
ma
ss
co
st
(€/o
dt)
Biomass yield (odt/ha.year)
Tall wheatgrass Palencia
Tall wheatgrass Soria
Tall wheatgrass Girona
Triticale
Rye
Oat
Lopsided Oat
Figure 4: Biomass costs production at the farm level in
Tall wheatgrass and winter cereals
Table VIII: main costs for biomass from three scenarios
of Tall wheatgrass and for winter cereals considered in
this study Winter cereals
€/ha.y-1
Regions/inputs Palencia Girona Soria (Soria and León)
Field works 19 18 16 164
base fertilization 13 0 0 157
Top fertilization 70 54 35 70
Pre emergence herbicides 1 8 13 0
Reposition fertilization 8 2 0 0
Post emergence herbicides 1 2 1 51
Final herbicides 2 2 2 0
Rental land 119 174 90 119
Mowing, baling and loading 156 153 153 163
Seeds 5 5 5 114
Total 393,58 418,53 314,18 838,00
Tall wheatgrass (€/ha.y-1)
Considering the biomass yields explored range in our
scenarios, Tall wheatgrass produced lower costs at all
yields but differences were higher (as much as 124€/odt)
when biomass yield was lower (below 4odt/ha). Highest
yields showed a lower cost for Tall wheatgrass (around
36€/odt) suggesting that more productive areas may be
also better suited for the perennial grass.
Total mean costs per hectare considering 15 years
lifetime of Tall wheatrgrass, were much higher that
winter cereals in all scenarios (Table VIII). The higher
costs of winter cereals might be explained mainly because
of a higher contribution of establishment (machinery
operations, base fertilization and sowing). Rental lands
contribution, top fertilization and harvest operations
(mowing, baling and loading) are major costs affecting
Tall wheatgrass.
3.2. Global warming potential
Increasing yields reflect a remarkable reduction in
GHG emissions when producing electricity in a power
energy plant. Nevertheless, winter cereals had higher
GWP at similar yields at the farm level compared to Tall
wheatgrass. As reflected with mean production costs,
lower yields achieved higher GWP per TJ in winter
annual grasses compared to Tall wheatgrass (Figure 5).
0
20
40
60
80
100
120
2000 4000 6000 8000 10000 12000 14000
GW
P (
Mg
CO
2 e
q T
J e
lect
rcit
y-1
)
Yield (kg d.m. ha-1)
Oat
Lopsided Oat
Rye
Triticale
Tall wheatgrass
(Soria)
Tall wheatgrass
(Palencia)
Tall wheatgrass
(Gerona)
Figure 5: Global warming potentials as function of
biomass yields per hectare in winter cereals and Tall
wheatgrass scenarios.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
2000 4000 6000 8000 10000 12000 14000
GH
G S
avin
gs
(%)
Bio
ma
ss C
om
pa
red
to
el
ectr
icit
y
from
Na
tura
l G
as
as
foss
il r
efer
ence
Yield (kg d.m. ha-1)
Oat
Lopsided Oat
Rye
Triticale
Tall wheatgrass
(Soria)
Tall wheatgrass
(Palencia)
Tall wheatgrass
(Gerona)
Tall wheatgrass
Figure 6: GHG emissions savings of Tall wheatgrass and
winter cereals producing electricity from biomass as a
function of biomass yield.
Page 9
0,2
0,6%
14,5
40,8%
13,4
37,6%
4,6
12,9%
2,3
6,4%
0,6
1,8%
Seed and Pesticides Fertilizers
Nitrous Oxide Field Works
Biomass transport Power Plant Operation
0,2
0,4%
21,7
50,2%
15,0
34,7%
3,5
8,0%
2,3
5,2%
0,6
1,5%
Seed and Pesticides Fertilizers
Nitrous Oxide Field Works
Biomass transport Power Plant Operation
0,1
0,4%
12,8
45,3%
10,0
35,4%
2,4
8,6%
2,3
8,0%
0,6
2,3%
Seed and Pesticides Fertilizers
Nitrous Oxide Field Works
Biomass transport Power Plant Operation
Soria
Palencia
Girona
Figure 7: Different contributions to the global warming
potentials for tall electric production (TJe) from biomass
of wheatgrass in the three study regions
Higher yields produced a higher emission reduction
when comparing GWP of electricity from biomass in the
25MW power energy plant, with natural gas electricity in
Spain (figure 6). As suggested in previous studies, winter
cereals low biomass yields at the farm level determine
higher GWP and lower emissions reductions replacing
the fossil reference. Even under extremely low yield
scenarios (below 4odt/ha) calculated GHG emissions
savings were always higher than 50% and low and
medium yields scenarios in both Palencia and Soria, were
always above 60%. These results suggest that Tall
wheatgrass biomass used for electricity might be suitable
for areas with lower potential yields achieving similar
limitations stated in the sustainability criteria established
for biofuels in the RED.
As shown in Figure 7, most important inputs causing
GWP are fertilizer production and those derived from
fertilizer use (nitrous oxide), accounting in total for
89.9% in Palencia, 78.4% in Soria and 80.7% in Girona.
Differences are linked to the nitrogen fertilizer doses for
each case (see table II).
3.3. Energy balances
Energy yields increased significantly with biomass
production per hectare as most inputs variation is lower
than outputs, suggesting that specific conditions could be
(yearly climate differences or soil variability) could
generate different energy balance scenarios. Therefore,
climate and soil conditions determining yields might
cause large variations on energy balances as well. Tall
wheatgrass originate a similar response compared to
winter cereals, but with a parallel higher response when
correlating energy yields at the power energy plant with
biomass yields in the field (figure 9).
0,0
1,0
2,0
3,0
4,0
5,0
6,0
7,0
8,0
2000 4000 6000 8000 10000 12000 14000
En
erg
y o
utp
ut
per
fo
ssil
en
erg
y i
np
uts
(T
J e
lect
rict
y
TJ
fo
ssil
en
erg
y-1
)
Yield (kg d.m. ha-1)
Oat
Lopsided Oat
Rye
Triticale
Tall wheatgrass
(Soria)
Tall wheatgrass
(Palencia)
Tall wheatgrass
(Gerona)
Figure 9: Energy ratios for electricity production from
biomass of Tall wheatgrass and winter cereals scenarios
as a function of biomass yield
The scenario for the region of Soria clearly has a
higher energy yield at similar biomass yields in the farm
probably explained by lower fertilizer uses (figure 10).
Most important fossil input contributions were
fertilizers. Fossil energy inputs were mostly caused by
fertilizers: 46%, 59.8 and 50.7 in Soria, Palencia and
Girona respectively. Secondly, machinery fossil inputs
and raw materials (pesticides and seeds) were affecting
energy ratios as well.
3.4. Soil nitrogen balance
Nitrogen balances in the soil changed dramatically in
the scenarios assumed for tall wheatgrass as a function of
biomass yield (Figure 11). A clear negative relationship
between soil nitrogen balance and biomass yield seems to
be explained as nitrogen fertilizer uptakes are higher to
nitrogen applications then suggesting a necessarily soil
nitrogen extraction from the soil nitrogen stock. As
management scenarios defined in this study considered
same nitrogen doses for five different biomass yields,
higher biomass yields imply a higher nitrogen uptake
compared to lower yields (figure 12). This result suggest
that yields between 6 and 8 odt/ha resulted in assumed no
changes in soil nitrogen.
Page 10
0,002
1,0%
0,098
46,0%
0,067
31,5%
0,035
16,5%
0,011
5,0%
Seed and Pesticides Fertilizers
Field Works Biomass transport
Power Plant Operation
Soria
0,002
0,8%
0,146
59,8%
0,051
20,7%
0,035
14,4%
0,011
4,4%
Seed and Pesticides Fertilizers
Field Works Biomass transport
Power Plant Operation
Palencia
0,001
0,7%
0,085
50,7%
0,036
21,3%
0,035
21,0%
0,011
6,4%
Seed and Pesticides Fertilizers
Field Works Biomass transport
Power Plant Operation
Girona
Figure 10: Different contribution for energy fossil inputs
per TJe in the three study regions with Tall wheatgrass
-80
-60
-40
-20
0
20
40
60
0 2000 4000 6000 8000 10000 12000 14000
Nit
rog
en B
ala
nce
(k
g N
ha
-1)
Yield (kg d.m. ha-1)
Tall
wheatgrass
(Soria)
Tall
wheatgrass
(Palencia)
Tall
wheatgrass
(Gerona)
Figure 11: Soil nitrogen balances in the three regions
scenarios as a function of its biomass yields.
As mentioned in above sections, obtaining high GHG
emissions savings would probably mean that Tall
wheatgrass had enough high biomass (energy output) and
energy yield, compared to the GHG emissions incurred
for crop and post-harvest transport and processing
producing electricity. Nevertheless, our results indicate
that producing more biomass implies more nitrogen
uptake and a potential excessive soil nitrogen depletion
that should be addressed in a bioenergy sustainable
production. In Girona for instance, only very low yields
extracted less nitrogen than that supplied to the crop.
Highest GHG emission reductions coincide with soil
nitrogen depletion suggesting that an adequate nitrogen
management should be consider (more nitrogen fertilizers
may cause higher fossil inputs and lower emission
reductions but may allow soil nitrogen stability).
40%
45%
50%
55%
60%
65%
70%
75%
80%
85%
90%
-80 -60 -40 -20 0 20 40 60
GH
G S
av
ings
(%)
Co
mp
are
d t
o el
ectr
icit
y f
rom
Na
tura
l G
as
as
foss
il r
efer
ence
)
Nitrogen Balance (kg N ha-1)
Tall
wheatgrass
(Soria)
Tall
wheatgrass
(Palencia)
Tall
wheatgrass
(Gerona)
NITROGEN SURPLUSNITROGEN DEFICIT
Figure 12: GHG emissions savings as a function of soil
nitrogen balances.
Page 11
4 CONCLUSIONS
From the results obtained under the trial conditions, it
can be concluded that:
Tall wheatgrass has good prospects for energy in
view of the amount of biomass produced in less fertile
areas without too many inputs.
According to the obtained results, the mean
production costs of Tall wheatgrass at the farm level
ranged from 40-60 €/odt for low and medium yield
scenarios (5-7 odt/ha.year). These costs are lower than
those of winter cereals that should have maximum yields
in order to obtain similar biomass costs. Considering a
price of 75-85€/odt for square bales at the farm (loaded
on the truck), wheat grass have a potential profitability at
least for the scenarios defined in this study. This suggests
that Tall wheatgrass could be suitable to supply power
energy plants in Spain.
Considering the explored range of crop yields and
management conditions, GHG emissions savings when
using Tall wheatgrass biomass for producing electricity
are significantly higher (50-90%) of those of winter
cereals (5-70%). Energy yields of electricity production
where clearly higher when biomass was obtained from
perennial grasses (2.5-7.5) compared to those of
electricity from winter cereals biomass (1.5-3).
These results suggest that TW can have a significant
potential as energy crop in marginal lands in Spain.
Nitrogen fertilization have been observed to be the
most important input to be considered when producing
energy from the species under study. This is because
nitrogen fertilizer production requires a large amount of
energy, causing greenhouse gas N2O emissions and
having a significant negative impact on CO2 balance.
Another sustainability indicator considered in this
study was nitrogen balance that was linked with GHG
emissions savings of electricity from biomass in Tall
wheatgrass. As management techniques regarding base
fertilizers (NPK) and top fertilizer applications in spring
(calcium ammonia nitare, 27%) were different in each
site and the production was assumed to vary in five
scenarios, an impact on the soil nitrogen balance suggest
that soil must be considered when looking for
sustainability of perennial grasses. It would be important
to consider no only energy crop fertilizing and its impact
on biomass quality and emissions but also economic and
energy balances. Moreover, the interest lies on obtaining
maximum yields with a minimum emission impact, so it
is recommended to improve the efficiency in the use of
nitrogen by adjusting the dose, the optimal timing of
application, the type of fertilizer, etc., or the inclusion of
alternative crops like nitrogen fixing species (legumes) or
pasture mixes.
5 REFERENCES
[1] Fernández, J., 2009. Potencial agroenergético de la
agricultura española. Ambienta: La revista del Ministerio
de Medio Ambiente, ISSN 1577-9491, Nº. 87, 2009 ,
pags. 35-46
[2] Boletin Oficial del Estado (BOE). Royal decree
1/2012, Jan 27th. Establishment of interruption
measures and aids for new renewable energy, co-
firing an residues utilization facilities. Madrid. Spain.
Available (in Spanish) at:
http://www.boe.es/boe/dias/2012/01/28/pdfs/BOE-A-
2012-1310.pdf
[3] IDAE, 2010. National Action plan for renewable
energies in Spain (Plan de Acción Nacional de
Energías Renovables de España, PANER) 2011-
2020. Instituto de la Diversificación y el Ahorro
Energético (IDAE), Ministery of Industry and
commerce. Madrid. Spain. Available at: www.idae.es
[4] Maletta E. A de. V and JC. El potencial de las
gramíneas como cultivo energético en España. Vida
Rural, Núm. 325. 2011.
[5] Fischer, G., S. Prieler, H. van Velthuizenet, S. M.
Lensink, M.Londo & M. De Wit. 2010. Biofuel
production potentials in Europe: Sustainable use of
cultivated land and pastures. Part I: Land productivity
potentials." Biomass and Bioenergy 34(2): 159-172.
[6] Fischer G., S. Prieler, H. van Velthuizen, G. Berndes,
A. Faaij, M. Londo & M. de Wit-2010. Biofuel
production potentials in Europe: Sustainable use of
cultivated land and pastures, Part II: Land use
scenarios, Biomass and Bioenergy, Volume 34, Issue
2, A roadmap for biofuels in Europe, February 2010,
Pages 173-187
[7] Lewandowski, I. J. M. O. Scurlock, E. Lindvall y M.
Christou, 2003. The development and current status
of perennial rhizomatous grasses as energy crops in
the US and Europe, Biomass and Bioenergy, Volume
25, Issue 4, October 2003, Pages 335-361.
[8] EEA, 2006. How much bioenergy can Europe
produce without harming the environment? EEA
Report No 7/2006.
[9] EC 2009. Renewable Energy Directive 2009/28/EC
of the European Parliament and of the Council of 23
April 2009 on the promotion of the use of energy
from renewable sources and amending and
subsequently repealing Directives 2001/77/EC and
2003/30/EC. Available at:
http://europa.eu/legislation_summaries/energy/renew
able_energy/en0009_en.htm
[10] Petr Havlík, Uwe A. Schneider, Erwin Schmid,
Hannes Böttcher, Steffen Fritz, Rastislav Skalský,
Kentaro Aoki, Stéphane De Cara, Georg
Kindermann, Florian Kraxner, Sylvain Leduc, Ian
McCallum, Aline Mosnier, Timm Sauer, Michael
Obersteiner, Global land-use implications of first and
second generation biofuel targets, Energy Policy,
Volume 39, Issue 10, October 2011, Pages 5690-
5702.
[11] T.D. Searchinger, S.P. Hamburg, J. Melillo, W.
Chameides, P. Havlik, D.M. Kammen, G.E. Likens,
R.N. Lubowski, M. Obersteiner, M. Oppenheimer, G.
Philip Robertson, W.H. Schlesinger, G. David
Tilman. 2009.Fixing a critical climate accounting
error. Science, 326 (2009), pp. 527–528
[12] Faist M, Reinhard J, Zah R. RSB GHG Calculation
Methodology v 2.0. Roundtable on Sustainable
Biofuels; 2011.
[13] Martín C, Maletta E, Ciria P, Santos A, del Val MA,
Pérez P, González Y, Lerga P. Energy and
enviromental assessment of electricity production
from winter cereals biomass harvested in two
locations of Northern Spain. 19th European Biomass
Conference & Exhibition:From Research to Industry
and Markets, Berlin Germany: 2011.
Page 12
[14] Gasol CM, Gabarrell X, Anton A, Rigola M,
Carrasco J, Ciria P, Solano ML, Rieradevall J. Life
cycle assessment of a Brassica carinata bioenergy
cropping system in southern Europe. Biomass
Bioenergy 2007;31:543–55
[15] J. Goñi, A. Lafarga and P.Armesto. New cereal
varieties. Grupo para la evaluacion de las nuevas
variedades de cultivos extensivos en España –
GENVCE. Available at: www.genvce.org.
[16] European Parliament. 2010. The Single Payment
Scheme After 2013: New Approach-New Targets
Study. Available at:
http://www.europarl.europa.eu/studies
[17] Maletta E. A de. V and JC. El potencial de las
gramíneas como cultivo energético en España. Vida
Rural, Núm. 325. 2011.
[18] A Monti, P Venturi, H.W Elbersen, Evaluation of
the establishment of lowland and upland switchgrass
(Panicum virgatum L.) varieties under different
tillage and seedbed conditions in northern Italy, Soil
and Tillage Research, Volume 63, Issues 1–2,
December 2001, Pages 75-83, ISSN 0167-1987,
10.1016/S0167-1987(01)00238-0.
[19] Edward M.W. Smeets, Iris M. Lewandowski, André
P.C. Faaij, The economical and environmental
performance of miscanthus and switchgrass
production and supply chains in a European setting,
Renewable and Sustainable Energy Reviews, Volume
13, Issues 6–7, August–September 2009, Pages 1230-
1245, ISSN 1364-0321, 10.1016/j.rser.2008.09.006.
[20] P. Venturi, J.K. Gigler, W. Huisman, Economical
and technical comparison between herbaceous
(Miscanthus x giganteus) and woody energy crops
(Salix viminalis), Renewable Energy, Volume 16,
Issues 1–4, January–April 1999, Pages 1023-1026,
ISSN 0960-1481, 10.1016/S0960-1481(98)00363-2.
[21] M.Q. Qi, R.E. Redmann, Seed germination and
seedling survival of C3 and C4 grasses under water
stress, Journal of Arid Environments, Volume 24,
Issue 3, April 1993, Pages 277-285, ISSN 0140-
1963, 10.1006/jare.1993.1024.
[22] Asay, K. H. Wheatgrasses and wildryes: the
perennial triticeae. In R. F. Barnes, C. J. Nelson, K. J.
Moore, and M. Collins (Eds) Forages, Volume I.
The Science of Grassland Agriculture (5th edition).
Iowa State Press, Chapt. 30 pp 373-385
[23] Hafenrichter, A.L.,J.L. Schwendiman, H.L. Harris,
R.S. McLauchlan, and H.W.Miller. 1968. Grasses
and Legumes for Soil Conservation in the Pacific
Northwest and Great Basin Status. USDA Agric.
Handb.339. Washington, DC.: US Gov.Print.Off.
[24] Sándor Csete et al. Tall Wheatgrass CUltivar
Szarvasi-1 (Elymus elongatus subsp. ponticus cv.
Szarvasi-1) as a Potential Energy Crop for Semi-Arid
Lands of Eastern Europe. University of Pécs,
Hungary.
[25] Cálculo de los costes de operación de cultivos en
diferentes zonas agrícolas. Ministery of agricultura,
food and environment (MARM). Madrid. Spain.
Available at:
http://www.magrama.gob.es/app/mecanizacion/costes
OperacionCultivos.aspx
[26] C. Ojuez, A. Lauric R.Siolotto and O. Scheneiter.
Efecto del ambiente y densidad de siembra sobre la
implantación de agropiro alargado (Thinopyrum
ponticum (Podp.) Barkw. and Dewey)) en el norte de
la Provincia de Buenos Aires. 2011. Sitio Argentino
de Producción Animal. INTA. Est.Agr. Bordenave.
Available at: http://www.produccion-
animal.com.ar/produccion_y_manejo_pasturas/pastur
as%20artificiales/26-agropiro_alargado.pdf
[27] P. R. Salon, H. Mayton, J. Hansen, Martin van der
Grinten, and T. Horvath. 2009. Tall wheatgrass for
Biofeedstock Energy: Yield, Seeding Rate and Time
of Harvest Study. USDA-NRCS Big Flats Plant
Materials Center, Corning, NY and Cornell
University, Ithaca, NY 3USDA-NRCS Columbia SC.
Available at: http://www.plant-
materials.nrcs.usda.gov/pubs/nypmspo10049.pdf
[28] ISO. 14040:2006. Environmental management-Life
cycle assessment-Principles and framework.
European Committee for Standardization. 2006.
[29] ISO. 14044:2006. Environmental
Management–Life Cycle Assessment–Requirements
and Guidelines. European Committee for
Standardization. 2006.
[30] Goedkoop M, De Schryver A, Oele M, Sipke D, De
Roest D. Introduction to LCA with SimaPro 7.
Netherlands: PRé Consultants; 2010.
[31] Goedkoop M, De Schryver A, Oele M, others.
Introduction to LCA with SimaPro 7. PRé
Consultants Report 2008;4.
[32] Frischknecht R, Jungbluth N, Althaus HJ, Doka
G, Dones R, Hischier R, Hellweg S, Nemecek T,
Rebitzer G, Spielmann M. Overview and
Methodology. Final report ecoinvent data v2.0, No.
1. Dübendorf, Switzerland: Swiss Centre for Life
Cycle Inventories; 2007.
[33] Frischknecht R, Jungbluth N, Althaus H-J,
Doka G, Dones R, Heck T, Hellweg S, Hischier R,
Nemecek T, Rebitzer G, Spielmann M. The ecoinvent
Database: Overview and Methodological Framework
(7 pp). The International Journal of Life Cycle
Assessment 2005;10:3–9.
[34] Nemecek T, Kägi T, Blaser S. Life Cycle Inventories
of Agricultural Production Systems. Final report
ecoinvent data v2.0, No. 15. Dübendorf, Switzerland:
Swiss Centre for Life Cycle Inventories; 2007.
[35] Emmenegger M. F., Heck T, Jungbluth N. Erdgas.
In: Sachbilanzen von Energiesystemen: Grundlagen
für den ökologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in
Ökobilanzen für die Schweiz (ed. Dones R.). Final
report ecoinvent data v2.0, No. 6-V. Dübendorf,
Switzerland: Swiss Centre for Life Cycle Inventories;
2007.
[36] Spielmann M, Dones R, Bauer C. Life Cycle
Inventories of Transport Services. Final report
ecoinvent data v2.0, No. 14. Dübendorf, Switzerland:
Swiss Centre for Life Cycle Inventories; 2007.
[37] De Klein C, Novoa RSA, Ogle S, Keith A S,
Rochette P, Wirth TC. Chapter 11:N2O Emissions
from Mananged soils, and CO2 emissions from Lime
and Urea Application. 2006 IPCC guidelines for
national greenhouse gas inventories Volume 4:
Agriculture, Forestry and Other Land Use, 2006
[38] Davis J, Haglund C. Life cycle inventory (LCI) of
fertilizer production. Fertilizer products used in
Sweden and Western Europe (SIK Rep. No. 654).
Swedish Institute for Food and Biotechnology,
Gothenburg, Sweden 1999.
Page 13
[39] Sutter J. Life Cycle Inventories of Pesticides. Final
report ecoinvent v2.2. St. Gallen, Switzerland: Swiss
Centre for Life Cycle Inventories; 2010
[40] Narain M, Singh BPN. Energy profile of a seed-
processing plant. Applied Energy 1988;30:227–34
[41] Jungbluth N. Erdöl. In: Sachbilanzen von
Energiesystemen: Grundlagen für den ökologischen
Vergleich von Energiesystemen und den Einbezug
von Energiesystemen in Ökobilanzen für die Schweiz
(ed. Dones R.). Final report ecoinvent data v2.0, No.
6-IV. Dübendorf, Switzerland: Swiss Centre for Life
Cycle Inventories; 2007.
[42] SAEFL. Handbuch Offroad-Datenbank. Swiss
Agency for the Environment, Forests and Landscape
(SAEFL) 2000.
[43] García CA, Fuentes A, Hennecke A, Riegelhaupt E,
Manzini F, Masera O. Life-cycle greenhouse gas
emissions and energy balances of sugarcane ethanol
production in Mexico. Applied Energy
2011;88:2088–97.
[44] EC-JRC-IES. International Reference Life Cycle
Data System (ILCD) Handbook - General guide for
Life Cycle Assessment - Provisions and Action Steps.
Fisrt edition. Luxembourg: Publications Office of the
European Union; 2010.
[45] Goedkoop M, De Schryver A, Oele M, Sipke D, De
Roest D. Introduction to LCA with SimaPro 7.
Netherlands: PRé Consultants; 2010.
[46] Althaus H.J., EMPA. IPCC 2007 method in:
Implementation of Life Cycle Impact Assessment
Methods. Final report ecoinvent v2.2 No. 3.
Dübendorf, Switzerland: Swiss Centre for Life Cycle
Inventories; 2010.
[47] Cuttle S, Shepherd M, Goodlass G. A review of
leguminous fertility-building crops, with particular
refence to nitrogen fixation and utilisation. Written as
part of DEFRA project OF0316 «The development of
improved guidance on the use of fertilitybuilding
crops in organic farming». Department for
Environment, Food and Rural affairs. UK. Internet:
http://www.organicsoilfertility.co.uk/reports/index.ht
ml2003
.[48] Jungbluth N, Esu-services, Frischknecht R,
Ecoinvent-Centre, EMPA. Cumulative energy
demand method in: Implementation of Life Cycle
Impact Assessment Methods. Final report ecoinvent
v2.2 No. 3. Dübendorf, Switzerland: Swiss Centre for
Life Cycle Inventories; 2010.
6 ACKNOWLEDGEMENTS
This work has been developed in the framework of
the Spanish National and Strategic Project `On Cultivos’
co-funded by the Spanish Ministry of Economy and
Competitiveness and the European Funds for Regional
Development (ERDF).under the dossier PSE-120000-
2009-15
7 LOGO SPACE